A Regression Based Multi Parameter Soil and Water Quality Model for Maize yield prediction

The ground water quality is the major contributing factor for sustainable crop production. But, routine chemical analysis of ground water and soil in a vast area is time consuming and integrated effect of soil and water quality on crop yield can not be obtained. Therefore, a study was conducted to characterize the ground water quality and its impact on soil characteristics and maize crop yield in Kothakunta watershed area at Wargal in Medak district of Andhra Pradesh, India. Based on the correlation studies between different water and soil quality parameters and crop yield, it was inferred that there was positive correlation between crop yield and pH of soil. It was negatively correlated with EC, RSC and Na. Hence, using multivariate statistical analysis, a multi parameter maize yield model was developed. The model quantified the relationship between independent variables (EC_iw, RSC_iw Na_iw and pH_soil) and dependent variable crop yield (Y). The independent variables (soil quality parameters and water quality parameters) which are significantly affecting the yield were decided from the correlation matrix developed for water and soil quality parameters. The yield model was statistically significant (R² = + 0.833) and can be used effectively to predict maize yield trend in the watershed.